Direct and Indirect Effects of Maternal, Paternal, and Offspring Genotypes: Trio-GCTA

Haplotype-based analysis distinguishes maternal-fetal genetic contribution to pregnancy-related outcomes

Genotype-based approaches for the estimation of SNP-based narrow-sense heritability ([Formula: see text]) have limited utility in pregnancy-related outcomes due to confounding by the shared alleles between mother and child. Here, we propose a haplotype-based approach to estimate the genetic variance attributable to three haplotypes - maternal transmitted ([Formula: see text]), maternal non-transmitted ([Formula: see text]) and paternal transmitted ([Formula: see text]) in mother-child pairs. We show through extensive simulations that our haplotype-based approach outperforms the conventional and contemporary approaches for resolving the contribution of maternal and fetal effects, particularly when m1 and p1 have different effects in the offspring. We apply this approach to estimate the explicit and relative maternal-fetal genetic contribution to the phenotypic variance of gestational duration and gestational duration-adjusted fetal size measurements at birth in 10,375 mother-child pairs. The results reveal that variance of gestational duration is mainly attributable to m1 and m2 ([Formula: see text]). In contrast, variance of fetal size measurements at birth are mainly attributable to m1 and p1 ([Formula: see text]). Our results suggest that gestational duration and fetal size measurements are primarily genetically determined by the maternal and fetal genomes, respectively. In addition, a greater contribution of m1 as compared to m2 and p1 ([Formula: see text]) to birth length and head circumference suggests a substantial influence of correlated maternal-fetal genetic effects on these traits. Our newly developed approach provides a direct and robust alternative for resolving explicit maternal and fetal genetic contributions to the phenotypic variance of pregnancy-related outcomes.

Direct and indirect genetic effects on early neurodevelopmental traits

BACKGROUND

Neurodevelopmental conditions are highly heritable. Recent studies have shown that genomic heritability estimates can be confounded by genetic effects mediated via the environment (indirect genetic effects). However, the relative importance of direct versus indirect genetic effects on early variability in traits related to neurodevelopmental conditions is unknown.

METHODS

The sample included up to 24,692 parent-offspring trios from the Norwegian MoBa cohort. We use Trio-GCTA to estimate latent direct and indirect genetic effects on mother-reported neurodevelopmental traits at age of 3 years (restricted and repetitive behaviors and interests, inattention, hyperactivity, language, social, and motor development). Further, we investigate to what extent direct and indirect effects are attributable to common genetic variants associated with autism, ADHD, developmental dyslexia, educational attainment, and cognitive ability using polygenic scores (PGS) in regression modeling.

RESULTS

We find evidence for contributions of direct and indirect latent common genetic effects to inattention (direct: explaining 4.8% of variance, indirect: 6.7%) hyperactivity (direct: 1.3%, indirect: 9.6%), and restricted and repetitive behaviors (direct: 0.8%, indirect: 7.3%). Direct effects best explained variation in social and communication, language, and motor development (5.1%-5.7%). Direct genetic effects on inattention were captured by PGS for ADHD, educational attainment, and cognitive ability, whereas direct genetic effects on language development were captured by cognitive ability, educational attainment, and autism PGS. Indirect genetic effects on neurodevelopmental traits were primarily captured by educational attainment and/or cognitive ability PGS.

CONCLUSIONS

Results were consistent with differential contributions to neurodevelopmental traits in early childhood from direct and indirect genetic effects. Indirect effects were particularly important for hyperactivity and restricted and repetitive behaviors and interests and may be linked to genetic variation associated with cognition and educational attainment. Our findings illustrate the importance of within-family methods for disentangling genetic processes that influence early neurodevelopmental traits, even when identifiable associations are small.

Using the phenotype differences model to identify genetic effects in samples of partially genotyped sibling pairs

The identification of causal relationships between specific genes and social, behavioral, and health outcomes is challenging due to environmental confounding from population stratification and dynastic genetic effects. Existing methods to eliminate environmental confounding leverage random genetic variation resulting from recombination and require within-family dyadic genetic data (i.e., parent-child and/or sibling pairs), meaning they can only be applied in relatively small and selected samples. We introduce the phenotype differences model and provide derivations showing that it-under plausible assumptions-provides consistent (and, in certain cases, unbiased) estimates of genetic effects using just a single individual's genotype. Then, leveraging distinct samples of fully and partially genotyped sibling pairs in the Wisconsin Longitudinal Study, we use polygenic indices and phenotypic data for 24 different traits to empirically validate the phenotype differences model. Finally, we utilize the model to test the effects of 40 polygenic indices on lifespan. After a 10% false discovery rate correction, we find that polygenic indices for three traits-body mass index, self-rated health, chronic obstructive pulmonary disease-have a statistically significant effect on an individual's lifespan.

Examining intergenerational risk factors for conduct problems using polygenic scores in the Norwegian Mother, Father and Child Cohort Study

The aetiology of conduct problems involves a combination of genetic and environmental factors, many of which are inherently linked to parental characteristics given parents' central role in children's lives across development. It is important to disentangle to what extent links between parental heritable characteristics and children's behaviour are due to transmission of genetic risk or due to parental indirect genetic influences via the environment (i.e., genetic nurture). We used 31,290 genotyped mother-father-child trios from the Norwegian Mother, Father and Child Cohort Study (MoBa), testing genetic transmission and genetic nurture effects on conduct problems using 13 polygenic scores (PGS) spanning psychiatric conditions, substance use, education-related factors, and other risk factors. Maternal or self-reports of conduct problems at ages 8 and 14 years were available for up to 15,477 children. We found significant genetic transmission effects on conduct problems for 12 out of 13 PGS at age 8 years (strongest association: PGS for smoking, β = 0.07, 95% confidence interval = [0.05, 0.08]) and for 4 out of 13 PGS at age 14 years (strongest association: PGS for externalising problems, β = 0.08, 95% confidence interval = [0.05, 0.11]). Conversely, we did not find genetic nurture effects for conduct problems using our selection of PGS. Our findings provide evidence for genetic transmission in the association between parental characteristics and child conduct problems. Our results may also indicate that genetic nurture via traits indexed by our polygenic scores is of limited aetiological importance for conduct problems-though effects of small magnitude or effects via parental traits not captured by the included PGS remain a possibility.

The structure of psychiatric comorbidity without selection and assortative mating

The widespread comorbidity observed across psychiatric disorders may be the result of processes such as assortative mating, gene-environment correlation, or selection into population studies. Between-family analyses of comorbidity are subject to these sources of bias, whereas within-family analyses are not. Because of Mendelian inheritance, alleles are randomly assigned within families, conditional on parental alleles. We exploit this variation to compare the structure of comorbidity across broad psychiatric polygenic scores when calculated either between-family (child polygenic scores) or within-family (child polygenic scores regressed on parental polygenic scores) in over 25,000 genotyped parent-offspring trios from the Norwegian Mother Father and Child Cohort study (MoBa). We fitted a series of factor models to the between- and within-family data, which consisted of a single genetic p-factor and a varying number of uncorrelated subfactors. The best-fitting model was identical for between- and within-family analyses and included three subfactors capturing variants associated with neurodevelopment, psychosis, and constraint, in addition to the genetic p-factor. Partner genetic correlations, indicating assortative mating, were not present for the genetic p-factor, but were substantial for the psychosis (b = 0.081;95% CI [0.038,0.124]) and constraint (b = 0.257;95% CI [0.075,0.439]) subfactors. When average factor levels for MoBa mothers and fathers were compared to a population mean of zero we found evidence of sex-specific participation bias, which has implications for the generalizability of findings from cohort studies. Our results demonstrate the power of the within-family design for better understanding the mechanisms driving psychiatric comorbidity and their consequences on population health.

Overcoming attenuation bias in regressions using polygenic indices

Measurement error in polygenic indices (PGIs) attenuates the estimation of their effects in regression models. We analyze and compare two approaches addressing this attenuation bias: Obviously Related Instrumental Variables (ORIV) and the PGI Repository Correction (PGI-RC). Through simulations, we show that the PGI-RC performs slightly better than ORIV, unless the prediction sample is very small (N < 1000) or when there is considerable assortative mating. Within families, ORIV is the best choice since the PGI-RC correction factor is generally not available. We verify the empirical validity of the simulations by predicting educational attainment and height in a sample of siblings from the UK Biobank. We show that applying ORIV between families increases the standardized effect of the PGI by 12% (height) and by 22% (educational attainment) compared to a meta-analysis-based PGI, yet estimates remain slightly below the PGI-RC estimates. Furthermore, within-family ORIV regression provides the tightest lower bound for the direct genetic effect, increasing the lower bound for the standardized direct genetic effect on educational attainment from 0.14 to 0.18 (+29%), and for height from 0.54 to 0.61 (+13%) compared to a meta-analysis-based PGI.

Heritability Estimation of Cognitive Phenotypes in the ABCD Study® Using Mixed Models

Twin and family studies have historically aimed to partition phenotypic variance into components corresponding to additive genetic effects (A), common environment (C), and unique environment (E). Here we present the ACE Model and several extensions in the Adolescent Brain Cognitive Development℠ Study (ABCD Study®), employed using the new Fast Efficient Mixed Effects Analysis (FEMA) package. In the twin sub-sample (n = 924; 462 twin pairs), heritability estimates were similar to those reported by prior studies for height (twin heritability = 0.86) and cognition (twin heritability between 0.00 and 0.61), respectively. Incorporating SNP-derived genetic relatedness and using the full ABCD Study® sample (n = 9,742) led to narrower confidence intervals for all parameter estimates. By leveraging the sparse clustering method used by FEMA to handle genetic relatedness only for participants within families, we were able to take advantage of the diverse distribution of genetic relatedness within the ABCD Study® sample.

Genetic nurture versus genetic transmission of risk for ADHD traits in the Norwegian Mother, Father and Child Cohort Study

Identifying mechanisms underlying the intergenerational transmission of risk for attention-deficit/hyperactivity disorder (ADHD) traits can inform interventions and provide insights into the role of parents in shaping their children's outcomes. We investigated whether genetic transmission and genetic nurture (environmentally mediated effects) underlie associations between polygenic scores indexing parental risk and protective factors and their offspring's ADHD traits. This birth cohort study included 19,506 genotyped mother-father-offspring trios from the Norwegian Mother, Father and Child Cohort Study. Polygenic scores were calculated for parental factors previously associated with ADHD, including psychopathology, substance use, neuroticism, educational attainment, and cognitive performance. Mothers reported on their 8-year-old children's ADHD traits (n = 9,454 children) using the Parent/Teacher Rating Scale for Disruptive Behaviour Disorders. We found that associations between ADHD maternal and paternal polygenic scores and child ADHD traits decreased significantly when adjusting for the child polygenic score (pΔβ = 9.95 × 10-17 for maternal and pΔβ = 1.48 × 10-14 for paternal estimates), suggesting genetic transmission of ADHD risk. Similar patterns suggesting genetic transmission of risk were observed for smoking, educational attainment, and cognition. The maternal polygenic score for neuroticism remained associated with children's ADHD ratings even after adjusting for the child polygenic score, indicating genetic nurture. There was no robust evidence of genetic nurture for other parental factors. Our findings indicate that the intergenerational transmission of risk for ADHD traits is largely explained by the transmission of genetic variants from parents to offspring rather than by genetic nurture. Observational associations between parental factors and childhood ADHD outcomes should not be interpreted as evidence for predominantly environmentally mediated effects.

Annual Research Review: Towards a deeper understanding of nature and nurture: combining family-based quasi-experimental methods with genomic data

Distinguishing between the effects of nature and nurture constitutes a major research goal for those interested in understanding human development. It is known, for example, that many parent traits predict mental health outcomes in children, but the causal processes underlying such associations are often unclear. Family-based quasi-experimental designs such as sibling comparison, adoption and extended family studies have been used for decades to distinguish the genetic transmission of risk from the environmental effects family members potentially have on one another. Recently, these designs have been combined with genomic data, and this combination is fuelling a range of exciting methodological advances. In this review we explore these advances - highlighting the ways in which they have been applied to date and considering what they are likely to teach us in the coming years about the aetiology and intergenerational transmission of psychopathology.

Maternal depression and the polygenic p factor: A family perspective on direct and indirect effects

Within-family studies typically assess indirect genetic effects of parents on children, however social support theory points to a critical role of partners and children on women's depression. To address this research gap and account for the high heterogeneity of depression, we calculated a general psychiatric factor using eleven major psychiatric polygenic scores (polygenic p), in up to 25,000 parent-offspring trios from the Norwegian Mother, Father and Child Cohort Study (MoBa). Multilevel modeling of trio polygenic p was used to distinguish direct and indirect genetic effects on mothers depression during pregnancy (gestational age 17 and 30 weeks), infancy (6 months, 18 months) and early childhood (3 years, 5 years, and 8 years). We found mothers polygenic p predicts their depression symptoms (b = 0.092; 95 % CI [0.087,0.098]), outperforming prediction using a single major depressive disorder polygenic score (b = 0.070, 95 % CI [0.066,0.075]). Jointly modeling trio polygenic p revealed indirect genetic effects of fathers (b = 0.022, 95 % CI [0.014,0.030]) and children (b = 0.021, 95 % CI [0.010,0.037]) on mothers' depression. Our results support the generalizability of polygenic effects across mental health and highlight the role of close family members on women's depression.

Do environmental effects indexed by parental genetic variation influence common psychiatric symptoms in childhood?

Parental genes may indirectly influence offspring psychiatric outcomes through the environment that parents create for their children. These indirect genetic effects, also known as genetic nurture, could explain individual differences in common internalising and externalising psychiatric symptoms during childhood. Advanced statistical genetic methods leverage data from families to estimate the overall contribution of parental genetic nurture effects. This study included up to 10,499 children, 5990 mother-child pairs, and 6,222 father-child pairs from the Norwegian Mother Father and Child Study. Genome-based restricted maximum likelihood (GREML) models were applied using software packages GCTA and M-GCTA to estimate variance in maternally reported depressive, disruptive, and attention-deficit hyperactivity disorder (ADHD) symptoms in 8-year-olds that was explained by direct offspring genetic effects and maternal or paternal genetic nurture. There was no strong evidence of genetic nurture in this sample, although a suggestive paternal genetic nurture effect on offspring depressive symptoms (variance explained (V) = 0.098, standard error (SE) = 0.057) and a suggestive maternal genetic nurture effect on ADHD symptoms (V = 0.084, SE = 0.058) was observed. The results indicate that parental genetic nurture effects could be of some relevance in explaining individual differences in childhood psychiatric symptoms. However, robustly estimating their contribution is a challenge for researchers given the current paucity of large-scale samples of genotyped families with information on childhood psychiatric outcomes.

Celebrating a Century of Research in Behavioral Genetics

A century after the first twin and adoption studies of behavior in the 1920s, this review looks back on the journey and celebrates milestones in behavioral genetic research. After a whistle-stop tour of early quantitative genetic research and the parallel journey of molecular genetics, the travelogue focuses on the last fifty years. Just as quantitative genetic discoveries were beginning to slow down in the 1990s, molecular genetics made it possible to assess DNA variation directly. From a rocky start with candidate gene association research, by 2005 the technological advance of DNA microarrays enabled genome-wide association studies, which have successfully identified some of the DNA variants that contribute to the ubiquitous heritability of behavioral traits. The ability to aggregate the effects of thousands of DNA variants in polygenic scores has created a DNA revolution in the behavioral sciences by making it possible to use DNA to predict individual differences in behavior from early in life.

Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study

The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partitioning the genetic covariation between birthweight and cardiometabolic traits into maternally mediated and offspring mediated contributions. We model the covariance between birthweight and later life outcomes, such as blood pressure, non-fasting glucose, blood lipids and body mass index in the Norwegian HUNT study, consisting of 15,261 mother-eldest offspring pairs with genetic and phenotypic data. Application of this model showed some evidence for maternally mediated effects of systolic blood pressure on offspring birthweight, and pleiotropy between birthweight and non-fasting glucose mediated through the offspring genome. This underscores the importance of genetic links between birthweight and cardiometabolic phenotypes and offer alternative explanations to environmentally based hypotheses for the phenotypic correlation between these variables.

Decomposing heritability and genetic covariance by direct and indirect effect paths

Estimation of heritability and genetic covariance is crucial for quantifying and understanding complex trait genetic architecture and is employed in almost all recent genome-wide association studies (GWAS). However, many existing approaches for heritability estimation and almost all methods for estimating genetic correlation ignore the presence of indirect genetic effects, i.e., genotype-phenotype associations confounded by the parental genome and family environment, and may thus lead to incorrect interpretation especially for human sociobehavioral phenotypes. In this work, we introduce a statistical framework to decompose heritability and genetic covariance into multiple components representing direct and indirect effect paths. Applied to five traits in UK Biobank, we found substantial involvement of indirect genetic components in shared genetic architecture across traits. These results demonstrate the effectiveness of our approach and highlight the importance of accounting for indirect effects in variance component analysis of complex traits.

The estimation of environmental and genetic parental influences

Parents share half of their genes with their children, but they also share background social factors and actively help shape their child's environment - making it difficult to disentangle genetic and environmental causes of parent-offspring similarity. While adoption and extended twin family designs have been extremely useful for distinguishing genetic and nongenetic parental influences, these designs entail stringent assumptions about phenotypic similarity between relatives and require samples that are difficult to collect and therefore are typically small and not publicly shared. Here, we describe these traditional designs, as well as modern approaches that use large, publicly available genome-wide data sets to estimate parental effects. We focus in particular on an approach we recently developed, structural equation modeling (SEM)-polygenic score (PGS), that instantiates the logic of modern PGS-based methods within the flexible SEM framework used in traditional designs. Genetically informative designs such as SEM-PGS rely on different and, in some cases, less rigid assumptions than traditional approaches; thus, they allow researchers to capitalize on new data sources and answer questions that could not previously be investigated. We believe that SEM-PGS and similar approaches can lead to improved insight into how nature and nurture combine to create the incredible diversity underlying human behavior.

On the importance of parenting in externalizing disorders: an evaluation of indirect genetic effects in families

BACKGROUND

Theoretical models of the development of childhood externalizing disorders emphasize the role of parents. Empirical studies have not been able to identify specific aspects of parental behaviors explaining a considerable proportion of the observed individual differences in externalizing problems. The problem is complicated by the contribution of genetic factors to externalizing problems, as parents provide both genes and environments to their children. We studied the joint contributions of direct genetic effects of children and the indirect genetic effects of parents through the environment on externalizing problems.

METHODS

The study used genome-wide single nucleotide polymorphism data from 9,675 parent-offspring trios participating in the Norwegian Mother Father and child cohort study. Based on genomic relatedness matrices, we estimated the contribution of direct genetic effects and indirect maternal and paternal genetic effects on ADHD, conduct and disruptive behaviors at 8 years of age.

RESULTS

Models including indirect parental genetic effects were preferred for the ADHD symptoms of inattention and hyperactivity, and conduct problems, but not oppositional defiant behaviors. Direct genetic effects accounted for 11% to 24% of the variance, whereas indirect parental genetic effects accounted for 0% to 16% in ADHD symptoms and conduct problems. The correlation between direct and indirect genetic effects, or gene-environment correlations, decreased the variance with 16% and 13% for conduct and inattention problems, and increased the variance with 6% for hyperactivity problems.

CONCLUSIONS

This study provides empirical support to the notion that parents have a significant role in the development of childhood externalizing behaviors. The parental contribution to decrease in variation of inattention and conduct problems by gene-environment correlations would limit the number of children reaching clinical ranges in symptoms. Not accounting for indirect parental genetic effects can lead to both positive and negative bias when identifying genetic variants for childhood externalizing behaviors.

Estimating effects of parents' cognitive and non-cognitive skills on offspring education using polygenic scores

Understanding how parents' cognitive and non-cognitive skills influence offspring education is essential for educational, family and economic policy. We use genetics (GWAS-by-subtraction) to assess a latent, broad non-cognitive skills dimension. To index parental effects controlling for genetic transmission, we estimate indirect parental genetic effects of polygenic scores on childhood and adulthood educational outcomes, using siblings (N = 47,459), adoptees (N = 6407), and parent-offspring trios (N = 2534) in three UK and Dutch cohorts. We find that parental cognitive and non-cognitive skills affect offspring education through their environment: on average across cohorts and designs, indirect genetic effects explain 36-40% of population polygenic score associations. However, indirect genetic effects are lower for achievement in the Dutch cohort, and for the adoption design. We identify potential causes of higher sibling- and trio-based estimates: prenatal indirect genetic effects, population stratification, and assortative mating. Our phenotype-agnostic, genetically sensitive approach has established overall environmental effects of parents' skills, facilitating future mechanistic work.

Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes

Maternal genetic effects can be defined as the effect of a mother's genotype on the phenotype of her offspring, independent of the offspring's genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5,178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347,980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.

Robust genetic nurture effects on education: A systematic review and meta-analysis based on 38,654 families across 8 cohorts

Similarities between parents and offspring arise from nature and nurture. Beyond this simple dichotomy, recent genomic studies have uncovered "genetic nurture" effects, whereby parental genotypes influence offspring outcomes via environmental pathways rather than genetic transmission. Such genetic nurture effects also need to be accounted for to accurately estimate "direct" genetic effects (i.e., genetic effects on a trait originating in the offspring). Empirical studies have indicated that genetic nurture effects are particularly relevant to the intergenerational transmission of risk for child educational outcomes, which are, in turn, associated with major psychological and health milestones throughout the life course. These findings have yet to be systematically appraised across contexts. We conducted a systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes. A total of 12 studies comprising 38,654 distinct parent(s)-offspring pairs or trios from 8 cohorts reported 22 estimates of genetic nurture effects. Genetic nurture effects on offspring's educational outcomes (βgenetic nurture = 0.08, 95% CI [0.07, 0.09]) were smaller than direct genetic effects (βdirect genetic = 0.17, 95% CI [0.13, 0.20]). Findings were largely consistent across studies. Genetic nurture effects originating from mothers and fathers were of similar magnitude, highlighting the need for a greater inclusion of fathers in educational research. Genetic nurture effects were largely explained by observed parental education and socioeconomic status, pointing to their role in environmental pathways shaping child educational outcomes. Findings provide consistent evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes, in addition to effects due to genetic transmission.

Systematic Review and Meta-analysis of Genetically Informed Research: Associations Between Parent Anxiety and Offspring Internalizing Problems

OBJECTIVE

Parent anxiety is associated with offspring internalizing problems (emotional problems related to anxiety and depression). This may reflect causal processes, whereby exposure to parent anxiety directly influences offspring internalizing (and/or vice versa). However, parent-offspring associations could also be attributable to their genetic relatedness. A systematic review and meta-analysis were conducted to investigate whether exposure to parent anxiety is associated with offspring internalizing after controlling for genetic relatedness.

METHOD

A literature search across 5 databases identified 429 unique records. Publications were retained if they used a quasi-experimental design in a general population sample to control for participant relatedness in associations between parent anxiety and offspring internalizing outcomes. Publications were excluded if they involved an experimental exposure or intervention. Studies of prenatal and postnatal anxiety exposure were meta-analyzed separately. Pearson's correlation coefficient estimates (r) were pooled using multilevel random-effects models.

RESULTS

Eight publications were retained. Data were drawn from 4 population cohorts, each unique to a quasi-experimental design: adoption, sibling-comparison, children-of-twins or in vitro fertilization. Cohorts were located in northern Europe or America. Families were predominantly of European ancestry. Three publications (Nfamilies >11,700; offspring age range, 0.5-10 years) showed no association between prenatal anxiety exposure and offspring internalizing outcomes after accounting for participant relatedness (r = .04; 95% CI: -.07, .14). Six publications (Nfamilies >12,700; offspring age range, 0.75-22 years) showed a small but significant association between concurrent symptoms in parents and offspring after accounting for participant relatedness (r = .13; 95% CI: .04, .21).

CONCLUSION

Initial literature, derived from homogeneous populations, suggests that prenatal anxiety exposure does not cause offspring internalizing outcomes. However, postnatal anxiety exposure may be causally associated with concurrent offspring internalizing via nongenetic pathways. Longitudinal stability, child-to-parent effects, and the role of moderators and methodological biases require attention.

Parental characteristics and offspring mental health and related outcomes: a systematic review of genetically informative literature

Various parental characteristics, including psychiatric disorders and parenting behaviours, are associated with offspring mental health and related outcomes in observational studies. The application of genetically informative designs is crucial to disentangle the role of genetic and environmental factors (as well as gene-environment correlation) underlying these observations, as parents provide not only the rearing environment but also transmit 50% of their genes to their offspring. This article first provides an overview of behavioural genetics, matched-pair, and molecular genetics designs that can be applied to investigate parent-offspring associations, whilst modelling or accounting for genetic effects. We then present a systematic literature review of genetically informative studies investigating associations between parental characteristics and offspring mental health and related outcomes, published since 2014. The reviewed studies provide reliable evidence of genetic transmission of depression, criminal behaviour, educational attainment, and substance use. These results highlight that studies that do not use genetically informative designs are likely to misinterpret the mechanisms underlying these parent-offspring associations. After accounting for genetic effects, several parental characteristics, including parental psychiatric traits and parenting behaviours, were associated with offspring internalising problems, externalising problems, educational attainment, substance use, and personality through environmental pathways. Overall, genetically informative designs to study intergenerational transmission prove valuable for the understanding of individual differences in offspring mental health and related outcomes, and mechanisms of transmission within families.